Geospatial data is becoming increasingly used in a variety of contexts associated with agriculture. For example, an agricultural biotechnology company or life sciences company may have many different business units which each collect geospatial data for various purposes. In addition, such an organization may collect other types of data which may not include geospatial data. Of course, other types of agriculture companies or other organizations may also collect such data, including those providing agricultural equipment, consulting, or information technology services.
In the context of a plant science or seed company, geospatial data may be collected to support a wide variety of business functions such as research, seed testing, seed production, and sales/marketing. In the research environment, it is often necessary or desirable to individually identify each plant within a research plot. Research plot location is identified by X, Y coordinates. The location of a plant within the plot can be thought of the Z axis or plant sequence number. In other words, the third plant in plot 110, 50. In hill plots or research schemes where the unit of interest is a single plant when a plant's location can be defined as an X, Y coordinate. One approach has been to define plant or plot location using a relative coordinate system that expresses location with respect to the first planted plot's location. Thus each plot was defined by plot or row number associated with a first axis (X axis) and a range number associated with a second axis (Y axis), the second axis perpendicular to the first axis. Thus each plant could be individually identified. This approach relies on the use of labeled stakes or plant tags to indicate the location of plots. The location of a plot or research experiment with respect to other plots or with surrounding fields was either undefined, or defined logically (difference in coordinates), or generally in terms of separation distance using manual means of establishing the distance from the edge of two experiments or parcels of land.
With such an approach, the creation of an actual physical map, if needed, showing the spatial relationships between an experiment and surrounding experiments or fields, would rely upon the manual preparation of a map. Such maps are not highly precise and may not always permit effective documentation of absolute distances required for regulatory compliance.
Research processes typically employ logical maps that show the positional relationship between one experiment and another and one plot with another. These maps do not describe actual physical location, i.e. longitude and latitude. They also fail to provide a means of accurately establishing distance from one plot to another or from one plot to regions of surrounding fields.
In the past, measuring wheels or tape measures were utilized to determine the distance between selected points and adjacent fields or experiments. These measurements provided relative distances, but were typically not able to establish absolute position because of the absence of a fixed and defined reference point. These measurements were of limited value for supporting downstream research processes because they were limited in number and not readily available for use in other applications or processes.
Thus, field research activities rely on tags or stakes to label plants, plots, or rows. To reduce labor it is common to label only selected plots or plants. During the various field activities it is possible to have a plot erroneously identified. This error is not readily detected. With the advent of molecular techniques for inserting novel genes into plants field research activities have become increasingly subject to regulatory requirements for planting at defined locations with adherence to business rules or regulatory requirements for genetic (pollen) isolation from non-regulated plants or fields. This isolation requirement is important for ensuring the containment of pollen that may serve as a source of “genetic contamination.” Manual methods for making and utilizing measurements preclude their widespread use in supporting research processes such as: planning; planting; stand counting; thinning; spectral or physiological characterization; tissue sampling; and harvest validation.
Research is merely one aspect associated with a seed business or life sciences company. Another aspect is production where plants are grown to provide sufficient seeds for commercialization. As previously mentioned, geospatial data associated with seed production activities may be collected by a seed company.
There are numerous problems associated with production. These include the isolation requirements discussed above with respect to research and other problems associated with identifying fields for use in production. In addition to these problems associated with production, there are also the problems that occur when production falls short, such as the problem of identifying potential alternative sources of seed, such as from a producer growing a particular hybrid or variety. In addition, to the problems associated with research and production, there are also problems associated with the marketing or sale of seed products. In particular, in the course of marketing or selling seed products, producers (customers) will often seek recommendations regarding which seed to plant on which fields. There is a desire to provide the best recommendations possible in order to satisfy customers. As previously mentioned, there may be geospatial data available to a seed company which is associated with sales and marketing, such as data acquired from demonstration plots or a producer.
What is needed is to provide geospatial data from multiple sources and to combine the data in order to increase the value and use of the data in activities such as, but not limited to seed research, product development, crop management, regulatory testing, regulatory approval, seed quality management, regulatory compliance, seed production, and related sales activities.